NIPS 2010 - Thinking dynamically
Apart from the presentations and posters, there is another great thing about NIPS: you can discuss machine learning with great researcher in person. One of the people I talked to quite a lot is Jascha Sohl-Dickstein . We discussed some deep methods and training procedures at some length and he is an amazing person with a lot of energy and new ideas. He recently wrote two papers that I quite liked: Minimum Probability Flow Learning and An Unsupervised Algorithm For Learning Lie Group Transformations . I like both of them for their quite unusual point of view. Jascha has a background in physics and his point of view focuses a lot on understanding the dynamics of learning and transformations. It think "Minimum Probability Flow Learning" gives new insights into training probabilistic models and as far as I know it is used quite successfully for training Ising models. Both works are not published yet but I find they are quite worth reading and so I'd like to draw a lit...